Branch point equipment configuration quantity calculation method and device, storage medium and program product

Abstract

The embodiment of the invention provides a network equipment configuration number calculation method and device, a storage medium and a program product, and the method comprises the steps: obtaining transaction behavior information when a user uses network equipment; based on the transaction behavior information, obtaining the business handling quantity of all website devices of the website in unit time and the business handling duration of each transaction; calculating a unit weighted business volume and a peak business volume of the website in unit time based on the business handling quantity and the business handling duration; and based on the unit weighted traffic and the peak traffic, calculating the daily average equipment configuration quantity of the network point by using a preset weight value. According to the method provided by the embodiment of the invention, the balance of the equipment demand quantity of the bank outlets in the peak time period and the daily time period can be realized, and the equipment operation cost of the outlets can be reduced while the queuing congestion in the peak time period is relieved.

Description

Technical Field

[0001] This application relates to the field of computer technology, specifically to a method, apparatus, storage medium, and program product for calculating the number of network equipment configurations. Background Technology

[0002] In addition to teller counters, bank branches have a large number of customer-facing devices that customers can use to conduct business. The more devices a branch has, the less likely there will be queues and the higher the customer satisfaction. However, this also increases operating costs.

[0003] Therefore, it is necessary to calculate the appropriate number of equipment to be configured at the branch locations in order to achieve a balance between operating costs and customer experience.

[0004] Current calculation methods have the following drawbacks: 1. The number of devices required for a branch can be calculated by collecting the average daily transaction volume of each device. However, since different customers have different business needs and the transaction time required for each business is different, this method is difficult to accurately calculate the number of devices that need to be configured. 2. Using the power-on or working time of the equipment to estimate the equipment's operating time, and then calculating the number of equipment to be configured, however, since the equipment at the branch needs to be kept running during business hours and provide services at any time, this method cannot accurately calculate the number of equipment to be configured. Summary of the Invention

[0005] The purpose of this application is to provide a method, apparatus, storage medium, and program product for calculating the number of network equipment configurations, in order to solve the above-mentioned problems.

[0006] To achieve the above objectives, the first aspect of this application provides a method for calculating the number of branch equipment configurations, comprising: obtaining transaction behavior information of users when using branch equipment; based on the transaction behavior information, obtaining the number of transactions processed by all branch equipment in the branch within a unit time and the transaction processing time of each transaction; based on the number of transactions processed and the transaction processing time, calculating the unit weighted transaction volume and peak transaction volume of the branch within a unit time; and based on the unit weighted transaction volume and peak transaction volume, calculating the average daily equipment configuration number of the branch with a preset weight value.

[0007] In this embodiment of the application, the transaction behavior information includes: the number of transactions for each branch device within a unit of time, the transaction trigger time when the user opens the page of the branch device for each transaction, the transaction completion time, the transaction exit time when the user closes the page of the branch device, and the business type of each transaction.

[0008] In the embodiment of the present application, the step of obtaining the number of service transactions of all the service facilities of the service site in a unit time and the service transaction time of each transaction based on the transaction behavior information comprises: obtaining the number of service transactions of each service facility in a unit time and the entering transaction page time and the returning home page time of the service facility in each transaction based on the transaction behavior information; and calculating the service transaction time of each transaction based on the entering transaction page time and the returning home page time.

[0009] In the embodiment of the present application, the step of calculating the service transaction time of each transaction comprises: if the previous user does not return to the home page of the service facility after the transaction ends and the current user starts the transaction, calculating the service transaction time of the previous transaction based on the transaction completion time and the transaction trigger time of the previous transaction in response to the completion of the current transaction; and calculating the service transaction time of the current transaction based on the transaction trigger time of the current transaction and the returning home page time of the current transaction.

[0010] In the embodiment of the present application, the step of calculating the service transaction time of each transaction further comprises: if the previous user does not return to the home page of the service facility after the transaction ends and the current user starts the transaction after a preset waiting time, calculating the service transaction time of the previous transaction based on the transaction completion time and the transaction trigger time of the previous transaction in response to the current transaction returning to the home page of the service facility; and calculating the waiting time from the end of the previous transaction to the current transaction returning to the home page of the service facility based on the returning home page time of the current transaction and the transaction completion time of the previous transaction.

[0011] In the embodiment of the present application, the step of calculating the unit weighted service volume of the service site in a unit time comprises: calculating the general transaction time of each type of service based on the number of service transactions and the service transaction time; calculating the reference transaction time of all services in a unit time based on the general transaction time of each type of service in a unit time; calculating the weight value of each type of service based on the reference transaction time and the general transaction time; and calculating the unit weighted service volume by weighting the number of service transactions in a unit time and the weight value of each type of service.

[0012] In the embodiment of the present application, the step of calculating the peak service volume of the network point in a unit time comprises: calculating the total device occupation time of each user when using the network point device based on the service handling quantity and the service handling time length; dividing the unit time into multiple sub-time periods, calculating the device occupation sub-time length of each sub-time period based on the total device occupation time length of each user in the unit time; selecting the time period with the longest time period among the total device occupation sub-time length in a preset proportion, calculating the median occupation sub-time length of the device occupation sub-time length of the selected total sub-time period; calculating the peak service volume based on the median occupation sub-time length and a preset idle coefficient.

[0013] In the embodiment of the present application, when the user information changes, the last transaction leaving time of the previous user before the user information changes is taken as the time when the previous user stops using the network point device, and the first transaction triggering time of the current user after the user information changes is taken as the time when the current user starts using the network point device.

[0014] In the embodiment of the present application, after the step of obtaining the transaction behavior information of the user when using the network point device, before the step of obtaining the service handling quantity and the service handling time length of each transaction of all network point devices of the network point in a unit time based on the transaction behavior information, the network point device configuration quantity calculation method further comprises: obtaining the median value of the handling time length of each type of service in a unit time based on the transaction behavior information; calculating the interquartile range value of the median value of the handling time length of each type of service, wherein the interquartile range value is the difference between the upper quartile and the lower quartile of the median value of the handling time length; calculating the transaction time length range threshold value of each type of service based on the interquartile range value; comparing the service handling time length of each type of service in each transaction with the corresponding transaction time length range threshold value, and eliminating the transaction information with the service handling time length not within the transaction time length range threshold value in the transaction behavior information.

[0015] In the embodiment of the present application, the step of calculating the daily average device configuration quantity of the network point based on the unit weighted service volume and the peak service volume with a preset weight value comprises: calculating the first configuration quantity of the corresponding network point device based on the unit weighted service volume with a preset first weight value; calculating the second configuration quantity of the corresponding network point device based on the peak service volume with a preset second weight value; calculating the daily average device configuration quantity of the network point based on the first configuration quantity and the second configuration quantity.

[0016] The second aspect of the application provides a bank point device configuration device, comprising: an acquisition module configured to obtain transaction behavior information of a user when using a point device; a data processing module configured to obtain, based on the transaction behavior information, a number of service transactions of all point devices of the point in a unit time and a service transaction time of each transaction; a first calculation module configured to calculate, based on the number of service transactions and the service transaction time, a unit weighted service volume and a peak service volume of the point in a unit time; and a second calculation module configured to calculate, based on the unit weighted service volume and the peak service volume, a daily average device configuration number of the point by using a preset weight value.

[0017] The third aspect of the application provides a machine readable storage medium, which stores instructions configured to cause a processor to perform the point device configuration number calculation method described above.

[0018] The fourth aspect of the application provides a computer program product, comprising a computer program configured to implement the point device configuration number calculation method described above.

[0019] Through the above technical solution, the actual use time of the point device in a period of time can be calculated according to different service types, and then a suitable device configuration number can be calculated by weighting the service volume of the point in peak time and daily time, so as to balance the device demand of the point in peak time and daily time, relieve the queuing congestion in peak time, and reduce the device operation cost of the point.

[0020] Other features and advantages of the embodiments of the application will be described in detail in the following specific embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0021] The accompanying drawings are used to provide a further understanding of the embodiments of the application, and constitute a part of the specification, and are used to explain the embodiments of the application together with the following specific embodiments, but do not constitute a limitation on the embodiments of the application. In the drawings: Figure 1 An application environment schematic diagram of the point device configuration number calculation method according to the embodiments of the application is schematically shown; Figure 2 A flowchart of the point device configuration number calculation method according to the embodiments of the application is schematically shown; Figure 3 A flowchart of step S110 of the point device configuration number calculation method according to the embodiments of the application is schematically shown; Figure 4 A flowchart of step S120 of the point device configuration number calculation method according to the embodiments of the application is schematically shown; Figure 5 A flowchart schematically showing step S130 of the method for calculating the number of bank outlet device configurations according to the embodiment of the present application is shown; Figure 6 A flowchart schematically showing step S140 of the method for calculating the number of bank outlet device configurations according to the embodiment of the present application is shown; Figure 7 A flowchart schematically showing step S140 of the method for calculating the number of bank outlet device configurations according to the embodiment of the present application is shown; Figure 8 A structural block diagram of the bank outlet device configuration device according to the embodiment of the present application is shown; Figure 9 An internal structural diagram of the computer device according to the embodiment of the present application is shown. DETAILED DESCRIPTION

[0022] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. It should be understood that the specific embodiments described herein are merely used to explain and illustrate the embodiments of the present application and should not be used to limit the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort belong to the scope of protection of the present application.

[0023] It should be noted that if the embodiments of the present application involve directional indications (such as up, down, left, right, front, back, etc.), the directional indications are merely used to explain the relative positional relationship, movement condition, etc. between components in a certain posture (as shown in the drawings), and if the certain posture changes, the directional indications also change accordingly.

[0024] In addition, if the embodiments of the present application involve descriptions of “first”, “second”, etc., the descriptions of “first”, “second”, etc. are merely for description purposes and should not be understood as indicating or implying the relative importance of the indicated technical features or implicitly indicating the number of the indicated technical features. Therefore, the features limited by “first”, “second” can explicitly or implicitly include at least one of the features. In addition, the technical solutions of the various embodiments can be combined with each other, but it must be based on the fact that a person of ordinary skill in the art can realize the combination, and when the combination of the technical solutions contradicts each other or cannot be realized, it should be considered that the combination of the technical solutions does not exist and is not within the scope of protection claimed by the present application.

[0025] The acquisition, transmission, storage, use, processing and the like of data in the technical solutions of the present application comply with relevant provisions of laws and regulations. In addition, it should be noted that in the embodiments of the present application, some existing industry solutions such as software, components, models and the like may be mentioned, which should be considered as exemplary, and the purpose is only to illustrate the feasibility of the implementation of the technical solutions of the present application, but it does not mean that the applicant has or will necessarily use the solutions.

[0026] The point device configuration quantity calculation method provided by the present application can be applied to the application environment as shown in Figure 1 . Among them, the terminal 110 communicates with the server 120 through the network, and the terminal 110 can be a point device. The transaction behavior information generated by the user when operating the point device can be sent to the server 120, so that the server 120 calculates the daily average device configuration quantity of the point according to the transaction behavior information. Among them, the server 120 can be realized by an independent server or a server cluster composed of multiple servers.

[0027] As shown in Figure 2 and Figure 7 , in an embodiment of the present application, a point device configuration quantity calculation method is provided. The point device configuration quantity calculation method of the present embodiment is mainly illustrated by taking the method applied to the server 120 in the above Figure 1 as an example. The point device configuration quantity calculation method of the present embodiment includes the following steps: Step S110, acquiring transaction behavior information of a user when using a point device.

[0028] In the present embodiment, the transaction behavior information includes: the number of transactions of each point device in a unit time, the transaction trigger time when the user opens the page of the point device in each transaction, the transaction completion time, the transaction leaving time when the user closes the page of the point device, and the business type of each transaction.

[0029] The present embodiment takes 24h as an example of a unit time. When the customer operates the point device to transact, the time when the main page of the point device is clicked to enter is the transaction trigger time, the time when the point device detects the completion of the transaction is the transaction completion time, and the time when the user clicks to close the main page of the point device after the transaction is completed is the transaction leaving time.

[0030] At the same time, the user may need to perform multiple transactions of different types when operating the point device, for example, the user will first operate the point device to perform a deposit business, then perform a transfer business to an account after the deposit is completed, and then continue to perform a transfer business to a second account after the first transfer operation is completed, and so on.

[0031] In the process, the network point device records the transaction trigger time, transaction completion time, transaction departure time, the number of transactions performed by the user and the service type of each transaction by obtaining the time when the corresponding operation occurs and the transaction code generated by each transaction.

[0032] As Figure 3 shown, in the embodiment of the present application, after step S110 and before step S120, the network point device configuration quantity calculation method further includes steps S111 to S114.

[0033] In step S111, based on the transaction behavior information, the median of the handling time of each type of service within a unit time is obtained.

[0034] In step S112, the interquartile range value of the median of the handling time of each type of service is calculated, wherein the interquartile range value is the difference between the upper quartile and the lower quartile of the median of the handling time.

[0035] In step S113, based on the interquartile range value, the transaction time range threshold of each type of service is calculated.

[0036] In step S114, the service handling time of each transaction of each type of service is compared with the corresponding transaction time range threshold, and the transaction information with service handling time outside the transaction time range threshold is removed from the transaction behavior information.

[0037] According to the above-mentioned action sequence of the user operating the network point device, it can be known that during the use of the network point device by the user, if some users stay on a certain page for too long (for example, the user does not return to the home page of the network point device after completing the transaction service, and the next user starts to handle the service after returning to the home page), the operation time of the last page of the previous user needs to be deducted at this time to remove abnormal data, so as to avoid inaccurate data of the transaction behavior information of the user in the statistics. The specific steps of removing abnormal data are as follows.

[0038] 1. Sort each transaction of the same transaction service type according to its service handling time to determine the median of the handling time of all transactions.

[0039] 2. Calculate the interquartile range IQR of the time data of each transaction service type, which is the difference between the upper quartile (Q3) and the lower quartile (Q1). That is: IQR = Q3 - Q1.

[0040] 3、Define the range of abnormal data: the transaction data whose business handling time is not within the transaction time range threshold is confirmed as abnormal data. The transaction time range threshold is: Q1-1.5*IQR to Q3+1.5*IQR, that is, the lower limit value of the transaction time range threshold is the lower quartile Q1 minus 1.5 times the interquartile range IQR, and the upper limit value is the upper quartile Q3 plus 1.5 times the interquartile range IQR.

[0041] 4、Compare the business handling time of each type of business in each transaction with the corresponding transaction time range threshold, and remove the transaction information in the transaction behavior information whose business handling time is not within the transaction time range threshold.

[0042] Step S120, based on the transaction behavior information, obtaining the number of business handling of all the point devices of the point in a unit time and the business handling time of each transaction.

[0043] As shown in Figure 4 in some embodiments, step S120 includes steps S121 to S122.

[0044] In step S121, based on the transaction behavior information, the number of business handling of each point device in a unit time, and the entering transaction page time and the returning home page time of the point device in each transaction are obtained.

[0045] In step S122, based on the entering transaction page time and the returning home page time, the business handling time of each transaction is calculated.

[0046] Further, the step of calculating the business handling time of each transaction includes: If the last user's transaction ends without returning to the home page of the point device and the current user starts the transaction, in response to the completion of the current transaction, the business handling time of the last transaction is calculated based on the transaction completion time and the transaction trigger time of the last transaction, and the business handling time of the current transaction is calculated based on the transaction trigger time of the current transaction and the returning home page time of the current transaction.

[0047] Further, the step of calculating the business handling time of each transaction further includes: after the last user's transaction ends, if the preset waiting time has elapsed and the home page of the point device has not been returned and the current user starts the transaction after returning to the home page of the point device, in response to the current transaction returning to the home page of the point device, the business handling time of the last transaction is calculated based on the transaction completion time of the last transaction and the transaction trigger time of the last transaction, and the waiting time from the end of the last transaction to the current transaction returning to the home page of the point device is calculated based on the returning home page time of the current transaction and the transaction completion time of the last transaction.

[0048] Specifically, when a user conducts a transaction on a point-of-presence device, the user usually operates the point-of-presence device in the following action sequence: The user opens page 1→ inputs page 1 related elements→ triggers transaction 1→ completes transaction 1→ the user leaves page 1; The user opens page 2→ inputs page 2 related elements→ triggers transaction 2→ completes transaction 2→ the user leaves page 2; … The user opens page n→ inputs page n related elements→ triggers transaction n→ completes transaction n→ the user leaves page n; The user completes all transactions and returns to the homepage of the point-of-presence device.

[0049] As can be seen, when a user uses a point-of-presence device, a complete user transaction process is formed from the time when the user first opens a page of the point-of-presence device to the time when the user returns to the homepage of the point-of-presence device after completing a transaction, and the point-of-presence device is considered to be occupied within the time range.

[0050] Therefore, the length of time that each user occupies the point-of-presence device, i.e., the transaction length T1 of each user when using the point-of-presence device, is T11, the time when the user finally returns to the homepage of the point-of-presence device, minus T12, the time when the user enters page 1. In the process of each user using the point-of-presence device, multiple transactions can occur, and the length of time T2 of each transaction is T21, the transaction completion time of the current transaction, minus T22, the time when the user opens page n of the current transaction.

[0051] When a user uses a point-of-presence device, the following situation can occur: the previous user does not return the point-of-presence device to the homepage after completing a transaction and leaves directly, and the current user directly conducts a transaction on the page.

[0052] In this case, the current user operates the point-of-presence device in the following action sequence: The user inputs page 1 related elements→ triggers transaction 1→ completes transaction 1→ the user leaves page 1; The user opens page 2→ inputs page 2 related elements→ triggers transaction 2→ completes transaction 2→ the user leaves page 2; … The user opens page n→ inputs page n related elements→ triggers transaction n→ completes transaction n→ the user leaves page n; The user completes all transactions and returns to the homepage of the point-of-presence device.

[0053] It can be seen that since the previous user does not return to the homepage, the current operation on the same page is another user's operation, for the current user, the operation of opening the page of the terminal device at the first transaction is missing, therefore, the specific leaving time of the previous user cannot be obtained, and the starting transaction time of the current user cannot be obtained, therefore, the last occupied time, i.e., the service handling time, needs to be corrected as: The service handling time T1=T(the transaction completion time T11 of the last transaction completed by the previous user)-the transaction trigger time T12 of the first transaction of the previous user; Since the time when the current user enters the page cannot be obtained, the current device occupation, i.e., the service handling time of the current user, is corrected as: The service handling time T2 of the current user=the return homepage time T21 of the current user-the transaction trigger time T22 of the first transaction of the current user.

[0054] When the previous user handles the service and does not return to the homepage, the current user clicks to return to the homepage and then starts to handle the transaction service, in this case, the current user operates the terminal device according to the following action sequence: The user returns to the homepage of the terminal device; The user opens page 1→the user inputs page 1 related elements→triggers transaction 1→completes transaction 1→the user leaves page 1; The user opens page 2→inputs page 2 related elements→triggers transaction 2→completes transaction 2→the user leaves page 2; … The user opens page n→inputs page n related elements→triggers transaction n→completes transaction n→the user leaves page n; The user completes all transactions and returns to the homepage of the terminal device.

[0055] In this case, when the user returns to the homepage of the terminal device, based on the transaction completion time of the last transaction and the transaction trigger time of the last transaction, the service handling time of the last transaction of the previous user in using the terminal device is calculated, i.e., the time length of the last transaction, and the device occupation time of the previous user can also be calculated through the transaction trigger time when the previous user enters the page at the first transaction and the transaction completion time when the last transaction is completed.

[0056] The waiting time from the end of the last transaction to the return of the current transaction to the homepage of the terminal device can also be calculated based on the return homepage time of the current transaction and the transaction completion time of the last transaction, the waiting time is taken as the idle time when there is no user, and the accuracy of the calculated service handling time is ensured.

[0057] Specifically, in the embodiment of the present application, when the user information of the user using the point device changes, the last transaction leaving time of the previous user before the user information changes is taken as the time when the previous user ends using the point device, and the first transaction triggering time of the current user after the user information changes is taken as the time when the current user starts using the point device.

[0058] In step S130, the unit weighted business volume and the peak business volume of the point in a unit time are calculated based on the business handling quantity and the business handling time length.

[0059] As shown in FIG. 13, in some embodiments, step S130 includes steps S131 to S134. Figure 5

[0060] In step S131, the general handling time length of each type of business is calculated based on the business handling quantity and the business handling time length.

[0061] In step S132, the reference handling time length of all businesses in a unit time is calculated based on the general handling time length of each type of business in a unit time.

[0062] In step S133, the weight value of each type of business is calculated based on the reference handling time length and the general handling time length.

[0063] In step S134, the business handling quantity in a unit time is weighted with the weight value of each type of business to obtain the unit weighted business volume.

[0064] In the embodiment, since the complexity of different types of businesses is different, the time consumed by each business handling is also different, therefore, only the pure statistics of the business quantity cannot accurately calculate the time consumed by the user when handling the business, the embodiment of the present application calculates the weight value of each type of business to accurately calculate the time length consumed by the user handling all types of businesses, and the specific steps are as follows.

[0065] The business handling quantity obtained in a unit time and the business handling time length of each type of transaction business are grouped according to the business type, arranged according to the length of the time consumed by the user, the median of the handling time length of each type of transaction business is taken as the general handling time length of the type of transaction business, and the number of handling of the type of transaction business is obtained.

[0066] Meanwhile, the average handling time length is calculated as the reference handling time length of all businesses in a unit time according to the business handling time length and the business handling quantity of all transaction businesses in a unit time.

[0067] Therefore, the weight value of each type of business is calculated as: =​ / t; The unit weighted business volume of each type of business is CW= ; wherein, is the weight value of each type of business, is the general handling time, and t is the reference handling time, is the number of transactions of each type of business, and CW is the unit weighted business volume of each type of business.

[0068] Further, it can be determined that, in the unit time, the unit weighted business volume is: N2=CW / Tn / TM; wherein, N2 is the unit weighted business volume, Tn is the number of transactions of all devices of the network point in the unit time, and TM is the proportion of the unit time in a day, i.e., when the unit time is 24h, TM is 1, and when the unit time is 12h, TM is 0.5.

[0069] In some embodiments, step S130 further comprises steps S135 to S138.

[0070] In step S135, based on the number of transactions and the transaction time, the total device occupation time of each user using the network point device is calculated.

[0071] In step S136, the unit time is divided into multiple sub-time periods, and based on the total device occupation time of each user in the unit time, the device occupation sub-time of each sub-time period is calculated.

[0072] In step S137, the longest time period of the selected preset proportion of the total device occupation sub-time is selected, and the median occupation sub-time of the device occupation sub-time of the selected sub-time period is calculated.

[0073] In step S138, based on the median occupation sub-time, the peak business volume is calculated with a preset idle coefficient.

[0074] Since the business handling time of the bank network point is relatively concentrated, when the transaction behavior information of the user using the network point device is counted, the transaction behavior information in a time range is segmented according to a certain time interval (for example, every ten minutes is a sub-time period), the total device occupation time of the network point device of the bank network point in each sub-time period is calculated, the first preset proportion (for example, the first 1%) of the sub-time period with the longest device occupation time in the total sub-time period is selected as the peak time period, the median occupation sub-time MaxT of the device occupation sub-time of the selected sub-time period is calculated, and the median occupation sub-time MaxT reflects the device occupation time of the bank network point in the busiest time period.

[0075] Then, the idle coefficient n is defined, wherein the idle coefficient n can be adjusted according to the bank outlet level and the business type demand, and the highest occupancy time length ratio of the equipment in the peak time period is determined. For example, the idle coefficient n is 0.5, that is, in the peak time period of the bank outlet, such as in 10 minutes of a sub time period, the use time length of each outlet equipment cannot exceed 50%, that is, 5 minutes, so as to avoid the queuing congestion situation and cause the user waiting time to be too long.

[0076] Further, it can be determined that the peak business volume is: N1=MaxT / n; wherein N1 is the peak business volume, MaxT is the median occupancy sub time length, and n is the idle coefficient.

[0077] In step S140, the daily average equipment configuration quantity of the outlet is calculated based on the unit weighted business volume and the peak business volume with a preset weight value.

[0078] As shown in FIG. 1, in some embodiments, step S140 further includes steps S141 to S143. Figure 6 In step S141, the first configuration quantity of the corresponding outlet equipment is calculated based on the unit weighted business volume with a preset first weight value.

[0079] In step S142, the second configuration quantity of the corresponding outlet equipment is calculated based on the peak business volume with a preset second weight value.

[0080] In step S143, the daily average equipment configuration quantity of the outlet is calculated based on the first configuration quantity and the second configuration quantity.

[0081] In this embodiment, according to the unit weighted business volume and the peak business volume calculated above, the first weight value and the second weight value corresponding thereto can be selected according to the actual business demand, and then the first configuration quantity and the second configuration quantity are calculated according to the following formula:

[0082] N=Wt1*N1+Wt2*N2; wherein Wt1 is the first weight value of the peak business volume, Wt2 is the second weight value of the unit weighted business volume, therefore, the first configuration quantity is Wt1*N1, the second configuration quantity is Wt2*N2, and finally the daily average equipment configuration quantity of the outlet is calculated, so as to balance the required outlet equipment configuration quantity in the peak time period and other time periods.

[0083] ​By the network point device configuration quantity calculation method described above, the actual use time of the network point device in a period of time can be calculated according to different service types, and then the appropriate device configuration quantity can be calculated according to the service quantity of the network point in the peak time and the daily time, so as to balance the device demand of the network point in the peak time period and the daily time period, relieve the queuing congestion in the peak time period, and reduce the device operation cost of the network point.

[0084] It should be understood that, although Figure 2 to Figure 7 The steps in the flowchart of the method are shown in sequence according to the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other orders. Moreover, Figure 2 to Figure 7 At least part of the steps in the method can include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily sequential, but can be executed in rotation or alternation with other steps or at least part of the sub-steps or stages of other steps.

[0085] As shown in Figure 8 The application further provides a bank network point device configuration device 200, comprising an acquisition module 210, a data processing module 220, a first calculation module 230, and a second calculation module 240, wherein: The acquisition module 210 is configured to acquire transaction behavior information of a user when using a network point device.

[0086] The data processing module 220 is configured to acquire, based on the transaction behavior information, a service handling quantity of all network point devices of the network point in a unit time and a service handling time of each transaction.

[0087] The first calculation module 230 is configured to calculate, based on the service handling quantity and the service handling time, a unit weighted service quantity and a peak service quantity of the network point in a unit time.

[0088] The second calculation module 240 is configured to calculate, based on the unit weighted service quantity and the peak service quantity, a daily average device configuration quantity of the network point with a preset weight value.

[0089] The bank network point device configuration device 200 comprises a processor and a memory, and the acquisition module 210, the data processing module 220, the first calculation module 230, and the second calculation module 240 described above are stored in the memory as program units, and the processor executes the above-mentioned program modules stored in the memory to realize the corresponding functions.

[0090] The processor includes a core, and the core calls corresponding program units in the memory. The core can be one or more, and the functions of the above modules are realized by adjusting the core parameters.

[0091] The memory can include non-permanent memory in a computer readable medium, random access memory (RAM) and / or non-volatile memory such as read-only memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.

[0092] The embodiment of the present application further provides a machine readable storage medium, which stores instructions, and the instructions enable the processor to be configured to execute the above-mentioned network point device configuration quantity calculation method when executed by the processor.

[0093] In one embodiment, the bank network device configuration device 200 of the embodiment of the present application can be a computer device, which can be a server, and the internal structure diagram thereof can be as shown in Figure 9 The computer device includes a processor A01, a network interface A02, a memory (not shown in the figure) and a database (not shown in the figure) connected through a system bus. The processor A01 of the computer device is used to provide computing and control capabilities. The memory of the computer device includes an internal memory A03 and a non-volatile storage medium A04. The non-volatile storage medium A04 stores an operating system B01, a computer program B02 and a database (not shown in the figure). The internal memory A03 provides an environment for the operating system B01 and the computer program B02 in the non-volatile storage medium A04 to run. The database of the computer device is used to store data for executing the above-mentioned network point device configuration quantity calculation method. The network interface A02 of the computer device is used to communicate with an external terminal through a network connection. The computer program B02 is executed by the processor A01 to realize the above-mentioned network point device configuration quantity calculation method.

[0094] Those skilled in the art can understand that Figure 9 the structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0095] In one embodiment, the bank network device configuration device 200 provided by the present application can be realized in the form of a computer program, which can run on a computer device as shown in Figure 9 The memory of the computer device can store various program modules constituting the bank network device configuration device 200, such as Figure 8The collection module 210, the data processing module 220, the first calculation module 230 and the second calculation module 240 are shown. The computer program composed of various program modules enables the processor to execute the steps in the network device configuration quantity calculation method of various embodiments of the present application described in the specification.

[0096] The present application also provides a computer program product adapted to execute the program of the following method steps when executed on a data processing device: In step S110, transaction behavior information of a user when using a network device is acquired.

[0097] In step S120, based on the transaction behavior information, the service handling quantity of all network devices of the network in a unit time and the service handling time of each transaction are acquired.

[0098] In step S130, based on the service handling quantity and the service handling time, the unit weighted service quantity and the peak service quantity of the network in a unit time are calculated.

[0099] In step S140, based on the unit weighted service quantity and the peak service quantity, the daily average device configuration quantity of the network is calculated with a preset weight value.

[0100] The computer program product provided by the embodiments of the present application can calculate the actual use time of the network device in a period of time according to different service types by executing the above method steps, and then the appropriate device configuration quantity is calculated according to the service quantity weighting of the network in the peak time and the daily time, so as to balance the device demand quantity of the network in the peak time period and the daily time period, relieve the queuing congestion in the peak time period, and reduce the device operation cost of the network.

[0101] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can be in the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can be in the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code.

[0102] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof.

[0103] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof.

[0104] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof.

[0105] In one typical configuration, the computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0106] The memory can include non-persistent memory and / or volatile memory, such as a random access memory (RAM) including a cache area for the temporary storage of data. A

[0107] Computer-readable media includes permanent and non-permanent, movable and non-movable media that can implement information storage by any method or technology. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer-readable media does not include transitory media such as modulated data signals and carriers.

[0108] It should also be noted that the terms "comprising", "containing", or any other variant thereof are intended to cover a non-exclusive inclusion, such that a process, method, article or apparatus that comprises a list of elements does not only include those elements, but can also include other elements not expressly listed or inherent to such process, method, article or apparatus. Without more limitations, the element defined by the statement "comprising a" does not exclude the presence of additional identical elements in the process, method, article or apparatus that includes the element.

[0109] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application shall be included in the scope of claims of the present application.

Claims

1. A method for calculating the number of network equipment configurations, characterized in that, include: Obtain information on users' transaction behavior when using equipment at service outlets; Based on the transaction information, obtain the number of transactions processed by all equipment at the branch within a unit of time and the processing time of each transaction. Based on the number of transactions processed and the duration of the transactions, calculate the weighted average transaction volume and peak transaction volume of the branch within a unit of time. Based on the unit weighted business volume and the peak business volume, the average daily number of devices configured at the site is calculated using a preset weight value.

2. The method for calculating the number of network equipment configurations according to claim 1, characterized in that, The transaction information includes: The number of transactions per unit time for each of the aforementioned branch devices, the transaction trigger time when a user opens the page of the branch device during each transaction, the transaction completion time, the transaction exit time when the user closes the page of the branch device, and the business type of each transaction.

3. The method for calculating the number of network equipment configurations according to claim 2, characterized in that, The steps of obtaining the number of transactions processed by all equipment at the branch within a unit of time and the processing time of each transaction based on the transaction behavior information include: Based on the transaction behavior information, the number of transactions processed by each of the branch devices within a unit of time, as well as the time when the branch device enters the transaction page during each transaction and the time when it returns to the homepage after the transaction ends are obtained. The processing time for each transaction is calculated based on the time of entering the transaction page and the time of returning to the homepage.

4. The method for calculating the number of network equipment configurations according to claim 3, characterized in that, The steps for calculating the processing time for each transaction include: If the previous user did not return to the homepage of the branch device after completing their transaction and the current user begins a transaction, then in response to the completion of the current transaction, the processing time of the previous transaction is calculated based on the transaction completion time and the transaction trigger time of the previous transaction; and The processing time of the current transaction is calculated based on the transaction trigger time and the return time to the homepage of the current transaction.

5. The method for calculating the number of network equipment configurations according to claim 3, characterized in that, The steps for calculating the processing time for each transaction also include: If, after a preset waiting time, the user does not return to the homepage of the branch device after the previous user's transaction has ended, and the current user begins a transaction after returning to the homepage of the branch device, then the user returns to the homepage of the branch device in response to the current transaction. The processing time of the previous transaction is calculated based on the transaction completion time and the transaction trigger time of the previous transaction. Based on the return time to the homepage of the current transaction and the completion time of the previous transaction, calculate the waiting time from the end of the previous transaction until the current transaction returns to the homepage of the branch device.

6. The method for calculating the number of network equipment configurations according to claim 2, characterized in that, The steps for calculating the weighted average volume of business at this branch within a unit of time include: Based on the number of transactions processed and the processing time, calculate the typical processing time for each type of transaction; Based on the general processing time of each type of business within a unit of time, calculate the benchmark processing time of all businesses within a unit of time. Based on the benchmark processing time and the general processing time, calculate the weight value for each type of service; The unit weighted business volume is obtained by weighting the number of transactions processed per unit time with the weight value of each type of business.

7. The method for calculating the number of network equipment configurations according to claim 6, characterized in that, The steps for calculating the peak traffic volume of this branch within a unit of time include: Based on the number of transactions processed and the duration of the transactions, calculate the total time each user occupies the equipment at the branch. The unit time is divided into multiple sub-time periods, and the device occupancy sub-time period of each sub-time period is calculated based on the total device occupancy time of each user within the unit time period. Select the longest time period corresponding to the occupancy of all the device occupancy sub-time periods from all the selected sub-time periods, and calculate the median occupancy sub-time period of all the selected sub-time periods. The peak traffic volume is calculated based on the median occupancy time and a preset idle coefficient.

8. The method for calculating the number of network equipment configurations according to claim 7, characterized in that, When the user information of the user using the branch equipment changes, the last transaction departure time of the previous user before the change is taken as the time when the previous user ended using the branch equipment, and the first transaction trigger time of the current user after the change is taken as the time when the current user started using the branch equipment.

9. The method for calculating the number of network equipment configurations according to claim 1, characterized in that, After obtaining user transaction behavior information when using branch equipment, and before the step of obtaining the number of transactions processed by all branch equipment within a unit time and the transaction processing time of each transaction based on the transaction behavior information, the method further includes: Based on the transaction behavior information, obtain the median processing time for each type of business per unit time period; Calculate the interquartile range of the median processing time for each type of service, wherein the interquartile range is the difference between the upper quartile and the lower quartile of the median processing time; Based on the interquartile range value, calculate the transaction duration range threshold for each type of business; Compare the processing time of each type of business in each transaction with the corresponding transaction duration range threshold, and remove transaction information in the transaction behavior information whose processing time is not within the transaction duration range threshold.

10. The method for calculating the number of network equipment configurations according to claim 1, characterized in that, The step of calculating the average daily number of devices configured at the branch office based on the unit weighted traffic volume and the peak traffic volume, using a preset weight value, includes: Based on the unit weighted business volume, the first configuration quantity of the corresponding branch equipment is calculated using a preset first weight value; Based on the peak business volume, the second configuration quantity of the corresponding branch equipment is calculated using a preset second weight value; Based on the first configuration quantity and the second configuration quantity, calculate the average daily equipment configuration quantity of the site.

11. A bank branch equipment configuration device, characterized in that, include: The data acquisition module is used to obtain information on users' transaction behavior when using the equipment at the branch. The data processing module is used to obtain, based on the transaction behavior information, the number of transactions processed by all equipment at the branch within a unit of time and the processing time of each transaction; The first calculation module is used to calculate the weighted average business volume and peak business volume of the branch within a unit time based on the number of business transactions and the business transaction duration. The second calculation module is used to calculate the average daily number of devices configured at the site based on the unit weighted business volume and the peak business volume, using a preset weight value.

12. A machine-readable storage medium storing instructions thereon, characterized in that, When executed by a processor, this instruction causes the processor to be configured to perform the method for calculating the number of network equipment configurations according to any one of claims 1 to 10.

13. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for calculating the number of network equipment configurations according to any one of claims 1 to 10.

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